- Snowflake Schema
- Databricks
- SQL
- Big Data
- Data Quality
- Data Warehousing
- DevOps
- PySpark
- Python Programming
- Data Pipelines
- Apache Spark
- Data Processing
Spark, Hadoop, and Snowflake for Data Engineering
Completed by Muhammed Afthab Abdulla
October 30, 2024
29 hours (approximately)
Muhammed Afthab Abdulla 's account is verified. Coursera certifies their successful completion of Spark, Hadoop, and Snowflake for Data Engineering
What you will learn
Create scalable data pipelines (Hadoop, Spark, Snowflake, Databricks) for efficient data handling.
Optimize data engineering with clustering and scaling to boost performance and resource use.
Build ML solutions (PySpark, MLFlow) on Databricks for seamless model development and deployment.
Implement DataOps and DevOps practices for continuous integration and deployment (CI/CD) of data-driven applications, including automating processes.
Skills you will gain
